Uuncertainty-based scheduling of multi-chiller system with thermal energy storage under real-time prices

Real-time electricity prices are announced by utility companies as a part of demand response programs to ensure the lowest total cost of service for the customers. Under the real-time pricing strategy, the risk of price variation is shared between the customer and the service provider; therefore, residential customers can reduce their electricity payment through proper scheduling of the major energy consumption equipment. In residential complexes, chiller units are one of the major contributors to the buildings' overall energy consumption; consequently, optimal scheduling of their operation can be a promising step toward reducing the operational cost. In this study, a robust optimization method is developed for optimal operation of the multi-chiller system with chilled-water storage unit considering the uncertainty associated with the predicted real-time prices. The proposed method is evaluated on a case study consisting of four multi-chiller unit and one chilled-water storage unit to investigate the operational cost variation. Simulations are conducted in GAMS software, where the results showed that the proposed method can reduce the operational cost deviation resulted by uncertainty in electricity rates.